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BackgroundTo develop and validate a novel tool for predicting the development of malignant brain edema (MBE) in large vessel occlusion stroke patients after endovascular thrombectomy (EVT).MethodsWe used a prospectively registered population of EVT patients from three comprehensive stroke centers. The population was randomly divided into two subsets (7:3): a training cohort and an internal validation cohort. External validation was performed using the Endovascular Treatment for Acute Anterior Circulation Ischemic Stroke Registry in China (ACTUAL) database. MBE was defined as (1) hypodense parenchyma in at least 50% of the middle cerebral artery and signs of local brain swelling, and (2) a midline shift of ≥5 mm at the septum pellucidum or pineal gland with obliteration of the basal cisterns. The model was constructed using logistic regression analysis. The performance of the model was examined in terms of discrimination and calibration.ResultsAfter adjusting for other confounders, baseline National Institutes of Health Stroke Scale (NIHSS) and Alberta Stroke Program Early CT (ASPECT) scores, a clinical history of hypertension, collateral status, intravenous thrombolysis before thrombectomy, fasting blood glucose, reperfusion status, and occlusion site were found to be independent predictors of MBE. These variables were combined to create the ACORNS grading scale. The areas under the curve in receiver operating curve analysis were 0.850 (95% CI 0.816 to 0.884), 0.874 (95% CI 0.821 to 0.926), and 0.785 (95% CI 0.740 to 0.829) for the training, internal validation, and external validation cohorts, respectively, indicating good discriminative performance in the validation cohorts.ConclusionsThe ACORNS grading scale is an accurate and easily applicable model for the prediction of the development of MBE after EVT.

A developed large language model generated radiologic impressions from findings in radiology reports that are professionally and linguistically appropriate for a full spectrum of radiology examinations.

Through in-depth analysis of the definition and connotation of new urbanization quality, a new urbanization indicator system with typical representativeness and quantification is established, and a spatio-temporal coupling coordination model is constructed based on this indicator system, and model input is obtained through urban statistical yearbooks and relevant government year reports Data, complete the temporal-spatial coupling coordination analysis of new urbanization and economic development. Taking a province as an example, it has been experimentally verified that the quality of new urbanization in the province has developed rapidly from 2010 to 2014, and the quality of new urbanization has stagnated from 2014 to 2015. In 2018, the quality of new urbanization in the province has rapidly increased its comprehensive value.

With the vigorous development of the global economy, modern enterprises have agreed to implement green supply chain management. The evaluation and selection of green suppliers plays a vital role in successful green supply chain management. As a multi-attribute group decision-making green supplier selection problem, it is difficult to fully describe the evaluation factors using precise numerical values and classical fuzzy sets, so it cannot assist enterprise managers in making completely reasonable decisions. Therefore, this paper proposes a green supplier evaluation and selection method based on interval BPA-based intuitionistic fuzzy sets. First, build a green supplier evaluation index system based on the characteristics of the papermaking enterprise's suppliers. Then, the intuitionistic fuzzy number is used to express the indicators of the evaluator for each supplier, and the intuitionistic fuzzy information is integrated through the organic combination of the IIFWA integration operator and the structural entropy weight to obtain the comprehensive evaluation value of the evaluator. Finally, the interval BPA-based intuitionistic fuzzy set method ranks the candidate suppliers and determines the best green supplier. Applying this method to the field of green supplier evaluation and selection can provide an effective method for enterprises to select suppliers scientifically and reasonably, which has practical reference value and practical significance.

Limited by the lack of training spectral data in different kinds of tissues, the diagnostic accuracy of laser-induced breakdown spectroscopy (LIBS) is hard to reach the desired level with normal supervised learning identification methods. In this paper, we proposed to apply the predictive data clustering methods with supervised learning methods together to identify tissue information accurately. The meanshift clustering method is introduced to compare with three other clustering methods which have been used in LIBS field. We proposed the cluster precision (CP) score as a new criterion to work with Calinski-Harabasz (CH) score together for the evaluation of the clustering effect. The influences of principal component analysis (PCA) on all four kinds of clustering methods are also analyzed. PCA-meanshift shows the best clustering effect based on the comprehensive evaluation combined CH and CP scores. Based on the spatial location and feature similarity information provided by the predictive clustering, the PCA-Meanshift can improve diagnosis accuracy from less than 95% to 100% for all classifiers including support vector machine (SVM), k nearest neighbor (k-NN), soft independent modeling of class analogy (Simca) and random forests (RF) models.

Lithium (Li), as the lightest metal and the most important powerful material in battery fabrication, is widely used in many fields. The fast detection of Li is necessary for industrial application. The slow-speed detection methods, including atomic absorption spectroscopy and inductively coupled plasma mass spectroscopy with high accuracy and low limit of detection, are hard to utilize in in situ industrial control due to complex prepreparation of samples. Here, through the analysis of the typical spectrum line at Li I 670.79 nm, Li ions in water were detected quantitatively in 1 min, including sample preparation by laser-induced breakdown spectroscopy (LIBS) with filter paper as the adsorption substrate. The calibration curve by polynomial function fitting is used to predict the Li^+ concentration. The limit of detection (LOD) as low as 18.4 ppb is obtained, which is much lower than the results ever reported by using filter paper. The related factor R^2 reaches 99%, and the prediction error is lower than 2%, proving the fast and online monitor for Li^+ by LIBS is feasible. Furthermore, by comparison with the results with filter paper enrichment, the Li^+ detection from water directly shows higher LOD to 10.5 ppm. Moreover, the plasma images, by gate-controlled intensified charge-coupled device, illustrate a different morphology and evolution between that on water surface and filter paper surface through visual observation. This study provides experimental and theoretical experience in a fast way for the quantitative detection of the lightest metal ion (Li^+) in liquid.

BackgroundMalignant brain edema (MBE) is a devastating complication in ischemic stroke. Data on MBE in patients who have had mechanical thrombectomy (MT) are relatively scarce.ObjectiveTo investigate the incidence, predictors, and clinical outcomes of MBE in patients after MT.MethodsWe included 130 consecutive patients after MT caused by anterior circulation large vessel occlusion stroke, treated with MT. MBE was defined as a midline shift of ≥5 mm on the follow-up imaging within 72 hours after MT. Characteristics of patients at admission and details of treatment were collected. The 90-day modified Rankin scale score was used as a measure of functional outcomes.ResultsOf the 130 patients (age, 68.6±10.9 years; male, 50%), 35 (26.9%) patients developed MBE. The patients with MBE had a lower rate of functional independence (OR=7.831; 95% CI 1.731 to 35.427; p=0.008) and significantly higher mortality at 90 days (OR=7.958; 95% CI 2.274 to 27.848; p=0.001) than patients without MBE. In 104 (80%) patients with successful recanalization (modified Thrombolysis in Cerebral Infarction score of 2b–3), 24 (23.1%) patients exhibited MBE. After adjustment for confounding, ICA occlusion (OR=3.746; 95% CI 1.169 to 12.006; p=0.026) and worse collateral score (grade 1 vs grade 0: OR=0.727; 95% CI 0.192 to 2.753; p=0.638; grade 2 vs grade 0: OR=0.130; 95% CI 0.021 to 0.819; p=0.030) were significantly associated with the development of MBE, despite successful recanalization.ConclusionsMBE after MT is not uncommon and was related to poor functional outcomes. Localization of a vessel occlusion and collateral status may play a role in the development of MBE.

Purpose The efficacy and safety of tourniquets use during total knee arthroplasty (TKA) in patients with osteoarthritis remain debated. This updated systematic review and meta-analysis aimed to further evaluate the role of tourniquets use in patients undergoing TKA for knee osteoarthritis by introducing trial sequential analysis.Methods PubMed, Embase, and the Cochrane Library were searched. We used the Cochrane risk of bias tool for quality assessment. Statistical heterogeneity across studies was evaluated using Cochran’s Q and I2statistic. Meta-analysis was performed using Stata/SE 14.0, and trail sequential analysis was performed using TSA software version 0.9.5.10 Beta. In addition, qualitative summary was also used to describe results.Results 15 randomized controlled trials (RCTs) involving 1202 patients were included in the meta-analysis. The pooled results showed that tourniquet use during TKA significantly reduced intraoperative blood loss (mean difference (MD)= −123.84, 95% confidence interval (CI): −163.37 to −84.32, p< .001)and shortened operation time (MD = −4.71, 95% CI: −7.6 to −1.82, p= .001), but there were no significant differences in postoperative blood loss, calculated blood loss, total blood loss, transfusion rate (p= .939), and deep venous thrombosis (DVT) rate between the tourniquet and no-tourniquet groups. TSA confirmed that the result of operation time was false positive, but the results of other outcomes were conclusive. The results of qualitative summary showed conflicting findings in terms of pain, range of motion (RoM) and swelling ratio between the two groups.Conclusions Tourniquet use in patients receiving TKA for osteoarthritis benefits to reduce intraoperative blood loss but has no effect on postoperative blood loss, calculated blood loss, total blood loss, operation time, transfusion rate, and DVT rate. In addition, it remains unclear the difference between the tourniquet and non-tourniquet groups in terms of pain, RoM and swelling ratio.

Background.The development of Barrett's esophagus (BE) and Barrett's associated adenocarcinoma (BAA) in the rat after experimental inducement of esophageal reflux of gastric, bile, and pancreatic juice has been reported by others. The purpose of this study was to determine whether similar results could be demonstrated in the mouse model.